Critical aspects of potassium management in agricultural systems
Why this work is in the frame
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Bibliographic record
Abstract
Abstract. Fertilizer and manure application rate and timing are often based on the optimal nitrogen rate and not on potassium (K) requirements. This can lead to excess or shortage of K depending on the crop and rotation. In grass‐dominated agricultural production, including many organic farming systems, K has become a critical element, especially in areas dominated by coarse‐textured or organic soils. In this paper we review K management in relation to long‐term sustainability of both the soil resource and the production of crops of high yield and quality. One question for the future is whether we can adopt management options that favour efficient use of K and secure a sustainable future for global K reserves. For example, is it possible to enhance the release rate of K from soil mineral sources so that we require less fertilizer K from K‐bearing salt deposits? A reduction in external K inputs requires improved on‐farm recycling of K in order to reduce losses. We also need a better understanding of soil processes and soil‐plant interactions and decision‐support tools to predict the potential K release from mineral weathering. Certain areas dominated by young, clay‐rich soils can potentially supply enough K, whereas other areas with coarse sandy or organic soils have a very low weathering potential and would thus need external inputs of K.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it